Utilizing Memories of Different Operational Speeds in a Vast Storage Network

ABSTRACT

A computing device includes an interface configured to interface and communicate with a storage network, a memory that stores operational instructions, and a processing module operably coupled to the interface and memory such that the processing module, when operable within the computing device based on the operational instructions, is configured to perform various operations. A computing device receives a data access request for an encoded data slice associated with a data object, determines whether the encoded data slice is stored in the first memory and in response to a determination that the encoded data slice is not stored in the first memory, issues another data access request for the encoded data slice to a second memory, where the first memory includes access characteristics that are faster than the second memory. When a data access response including the encoded data slice is received from the second memory, a response including the encoded data slice is transmitted.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. § 120 as a continuation-in-part of U.S. Utility applicationSer. No. 17/099,916, entitled “Storage Unit Including Memories ofDifferent Operational Speeds for Optimizing Data Storage Functions”,filed Nov. 17, 2020, which is a continuation of U.S. Utility applicationSer. No. 16/169,628, entitled “Utilizing Fast Memory Devices To OptimizeDifferent Functions”, filed Oct. 24, 2018, issued as U.S. Pat. No.10,846,025 on Nov. 24, 2020, which is a continuation of U.S. Utilityapplication Ser. No. 15/362,615, entitled “Utilizing Fast Memory DevicesTo Optimize Different Functions”, filed Nov. 28, 2016, issued as U.S.Pat. No. 10,255,002 on Apr. 9, 2019, which claims priority pursuant to35 U.S.C. § 119(e) to U.S. Provisional Application No. 62/260,735,entitled “Accessing Copies Of Data Stored In A Dispersed StorageNetwork”, filed Nov. 30, 2015, all of which are hereby incorporatedherein by reference in their entirety and made part of the present U.S.Utility Patent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

Prior art data storage systems do not efficiently service all types ofdata access requests, data checks, and data status checks. For example,the response time of such communications between devices may beprohibitive in some data storage systems and based on some conditions.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of another embodiment of a dispersedstorage network (DSN) in accordance with the present invention;

FIG. 10 is a flowchart illustrating an example of retrieving an encodeddata slice in accordance with the present invention;

FIG. 11A is a schematic block diagram of an example of separatelyprovisioned memories within a computing device for different purposes inaccordance with the present invention;

FIG. 11B is a schematic block diagram of another example of separatelyprovisioned memories within a computing device for different purposes inaccordance with the present invention;

FIG. 12 is a diagram illustrating an embodiment of a method forexecution by one or more computing devices in accordance with thepresent invention;

FIG. 13 is a schematic block diagram of another embodiment of adispersed storage network (DSN) in accordance with the presentinvention;

FIG. 14 is a flowchart illustrating an example of enhancing dataretrieval performance in accordance with the present invention;

FIG. 15 is a schematic block diagram of another embodiment of a DSN inaccordance with the present invention;

FIG. 16A is a diagram illustrating an embodiment of a method forexecution by one or more computing devices in accordance with thepresent invention;

FIG. 16B is a diagram illustrating an embodiment of another method forexecution by one or more computing devices in accordance with thepresent invention; and

FIG. 16C is a diagram illustrating an embodiment of another method forexecution by one or more computing devices in accordance with thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-8. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (10)controller 56, a peripheral component interconnect (PCI) interface 58,an I0 interface module 60, at least one I0 device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 60 is shown inFIG. 6. As shown, the slice name (SN) 60 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of another embodiment 900 of adispersed storage network (DSN) that includes the distributed storageand task (DST) processing unit 16, the network 24 of FIG. 1, and a setof storage units 1-n such as based on SUs 36 such as with respect toFIG. 3 or FIG. 7. Each storage unit includes a processing module and/orcomputing core 26, a fast memory 910, and a memory 920. The memory 920may be implemented utilizing the various types of memory such as a harddrive and/or hard disk drive (HDD). The fast memory 910 may beimplemented utilizing the memory 920 with access characteristics thatare faster than the memory 920 (e.g., solid-state memory, random accessmemory (RAM), and/or any other fast memory 910 device). Each storageunit may be implemented utilizing a DST execution unit that may beimplemented utilizing the computing device 12, 14, 16, the managing unit18, and/or the integrity processing unit 20 such as with respect to FIG.1, a SU 36 such as with respect to FIG. 3 or FIG. 7, and/or any otherdevice implemented within a DSN to perform operations associated with aDST execution unit. The DSN functions to retrieve the encoded dataslice. In some examples, the fast memory 910 is characterized assubstantially and/or approximately faster-responsive, faster-accessible,faster-operative, etc. memory than the memory 920. As a specificexample, the fast memory 910 when implemented as solid state memory willbe faster-responsive, faster-accessible, faster-operative, etc. memorythan the memory 920 when implemented as a hard disk drive (HDD).

In an example of operation of the retrieving of the encoded data slice,the processing module 84 of the storage unit 1 accesses the fast memory910 to determine whether a slice 1-1 is stored in the memory 920 whenreceiving a read request for slice 1-1, where data has been dispersedstorage error encoded to produce a plurality of N sets of encoded dataslices 1-n for storage in the memories of the storage units, where theDST processing unit 16 sends, via the network 24, a set of read slicerequests 1-n that includes the read request for slice 1-1. Thedetermining includes at least one of accessing a slice name and statuslist in the fast memory 910, interpreting the list, and indicatingwhether the slice is stored in the memory 920 based on theinterpretation of the list. For example, the processing module 84indicates that the slice 1-1 is available for retrieval when theretrieved list from the fast memory 910 indicates that the slice 1-1 isstored in the memory 920. When the requested slice is stored in thememory 920, the processing module 84 of the storage unit 1 sends, viathe network 24, the requested slice 1-1 to the DST processing unit 16 asa read response of a set of read responses for slices 1-n.

The processing module 84 of the storage unit 2 accesses the fast memory910 of the storage unit 2 to determine whether a slice 2-1 is stored inthe memory 920 of the storage unit 2 when receiving a read request forslice 2-1. The determining includes at least one of accessing a slicename and status list in from fast memory 910 of the storage unit 2,interpreting the list, and indicating whether the slice is stored in thememory 920 of the storage unit 2 based on the interpretation of thelist. For example, the processing module 84 of the storage unit 2indicates that the slice 2-1 is not available for retrieval when theretrieved list from the fast memory of the storage unit 2 indicates thatthe slice 2-1 is not stored in the memory 920. When the requested sliceis not stored in the memory 920, the processing module 80 for thestorage unit 2 sends, via the network 24, a read response for slice 2-1to the DST processing unit 16, where the response indicates that therequested slice 2-1 is not available.

FIG. 10 is a flowchart illustrating an example of retrieving an encodeddata slice. The method 1000 includes a step 1010 where a processingmodule (e.g., of a storage unit) receives a read request for an encodeddata slice, where the read request includes one or more of a slice namea revision level, a memory identifier, a fast memory identifier, amemory address, and a fast memory address. The method 1000 continues atthe step 1020 where the processing module accesses a fast memory todetermine whether the encoded data slice is available. For example, theprocessing module accesses a slice name and status list within the fastmemory, interprets the slice name and status list, and indicates thatthe requested encoded data slice is available when the interpretationindicates that the encoded data slice is stored in a memory (e.g.,another memory). The method 1000 branches to the step 1042 where theprocessing module generates a read response indicating that the encodeddata slices not available when the encoded data slices not available.The method 1000 continues to the next step 1044 where the processingmodule accesses a memory to retrieve the encoded data slice when theencoded data slice is available.

When the encoded data slice is available, the method 1000 continues atthe step 1030 where the processing module accesses a memory to retrieveencoded data slice. For example, the processing module identifies amemory device, identifies an address of the identified memory device,and accesses the identified memory device at the identified at addressto retrieve encoded data slice. The method 1000 continues at the step1040 where the processing module sends the retrieved encoded data sliceto a requesting entity.

When the encoded data slice is not available, the method 1000 continuesat the step 1042 where the processing module generates a read responseindicating that the encoded data slice is not available. The generatingincludes producing the response to include one or more of the slicename, a revision level, and an indicator that the slices not available.The method 1000 continues at the step 1044 where the processing modulesends the read response to the requesting entity.

FIG. 11A is a schematic block diagram of an example 1101 of separatelyprovisioned memories within a computing device for different purposes inaccordance with the present invention. A computing device 12 or 16include fast memory/random access memory (RAM) 1110 (e.g., such as solidstate memory) and memory 1120 (e.g., a hard disk drive (HDD)). Ingeneral, the fast memory/RAM 1110 is any type of memory that is veryquickly responsive and can be accessed very quickly as opposed to moreconventional memory such as a HDD that is relatively more slowlyresponsive to accesses thereto.

In an example of operation and implementation, a computing deviceincludes an interface configured to interface and communicate with adispersed storage network (DSN), a memory that stores operationalinstructions, and a processing module operably coupled to the interfaceand memory such that the processing module, when operable within thecomputing device based on the operational instructions, is configured toperform various operations.

For example, computing device 12 or 16 receives from another computingdevice a data access request for an encoded data slice (EDS) associatedwith a data object. Note that the data access request includes a dataaccess request slice name for the EDS associated with the data object.Then, the computing device 12 or 16 compares the data access requestslice name with a plurality of slice names stored within the RAM,wherein the plurality of slice names are respectively associated with aplurality of encoded data slices (EDSs) stored within the HDD.

When the data access request slice name compares unfavorably with theplurality of slice names, the computing device 12 or 16 transmits anempty data access response that includes no EDS to the other computingdevice. When the data access request slice name compares favorably withat least one of the plurality of slice names, the computing device 12 or16 then transmits retrieves, from the HDD, an EDS of the plurality ofEDSs having a corresponding slice name that compares favorably with thedata access request slice name and transmits a data access response thatincludes the EDS of the plurality of EDSs having the corresponding slicename to the other computing device.

In some examples, note that the data object is segmented into aplurality of data segments, and a data segment of the plurality of datasegments is dispersed error encoded in accordance with dispersed errorencoding parameters to produce a set of encoded data slices (EDSs). Notethat each EDS of the set of EDS having a respective slice name, and theset of EDSs are distributedly stored among a plurality of storage units(SUs) within the DSN. A decode threshold number of EDSs are needed torecover the data segment, a read threshold number of EDSs provides forreconstruction of the data segment, and a write threshold number of EDSsprovides for a successful transfer of the set of EDSs from a first atleast one location in the DSN to a second at least one location in theDSN.

Note that the computing device may be located at a first premises thatis remotely located from at least one SU of the primary SUs or pluralityof secondary SUs the within the DSN. Also, note that the computingdevice may be of any of a variety of types of devices as describedherein and/or their equivalents including a SU of any group and/or setof SUs within the DSN, a wireless smart phone, a laptop, a tablet, apersonal computers (PC), a work station, and/or a video game device.Note also that the DSN may be implemented to include or be based on anyof a number of different types of communication systems including awireless communication system, a wire lined communication systems, anon-public intranet system, a public internet system, a local areanetwork (LAN), and/or a wide area network (WAN).

FIG. 11B is a schematic block diagram of another example 1102 ofseparately provisioned memories within a computing device for differentpurposes in accordance with the present invention. The computing device12 or 16 stores slice names (e.g., SN 1_1 through SN 1_Y) in the fastmemory/RAM 1110 (e.g., such as solid state memory) and stores encodeddata slices (EDSs) (e.g., EDS 1_1 through EDS 1_Y) in the memory 1120(e.g., a hard disk drive (HDD)). In general, any other desiredidentifiers may also be stored in the fast memory/RAM 1110

A computing device 12 or 16 include fast memory/random access memory(RAM) 1110 (e.g., such as solid state memory) and memory 1120 (e.g., ahard disk drive (HDD)). In general, the fast memory/RAM 1110 is any typeof memory that is very quickly responsive and can be accessed veryquickly as opposed to more conventional memory such as a HDD that isrelatively more slowly responsive to accesses thereto.

In an example of operation and implementation, the computing device 12or 16 compares a revision level for the EDS associated with the dataobject that is included within the data access request to a plurality ofrevision levels stored within the RAM. Note that the plurality ofrevision levels are associated respectively with the plurality of slicenames stored within the RAM. When the data access request slice namecompares unfavorably with the plurality of slice names and when therevision level for the EDS associated with the data object comparesunfavorably with the plurality of revision levels, the computing device12 or 16 transmits the empty data access response to the other computingdevice.

When the data access request slice name compares favorably with theplurality of slice names and when the revision level for the EDSassociated with the data object compares unfavorably with the pluralityof revision levels, the computing device 12 or 16 transmits the emptydata access response to the other computing device. When the data accessrequest slice name compares favorably with at least one of the pluralityof slice names and when the revision level for the EDS associated withthe data object compares favorably with at least one of the plurality ofrevision levels, then the computing device 12 or 16 retrieves, from theHDD, the EDS of the plurality of EDSs having the corresponding slicename that compares favorably with the data access request slice name anda corresponding revision level that compares favorably with the revisionlevel for the EDS associated with the data object. The computing device12 or 16 then transmits the data access response that includes the EDSof the plurality of EDSs having the corresponding slice name and thecorresponding revision level that compares favorably with the revisionlevel for the EDS associated with the data object to the other computingdevice.

In some examples, the data access request for the EDS associated withthe data object is based on any one or more of a check request involvingthe EDS associated with the data object, a read request involving theEDS associated with the data object, a write request involving the EDSassociated with the data object, a rebuild request involving the EDSassociated with the data object, a rebuild scanning request involvingthe EDS associated with the data object, a reallocation requestinvolving the EDS associated with the data object, a rebalancing requestinvolving the EDS associated with the data object, a synchronizationrequest between mirrored vault operations involving the EDS associatedwith the data object, and/or a trimmed write request involving the EDSassociated with the data object based on fewer than all of a set ofencoded data slices (EDSs) generated when the data object is segmentedinto a plurality of data segments and a data segment of the plurality ofdata segments is dispersed error encoded in accordance with dispersederror encoding parameters to produce the set of EDSs.

Note that different sets of trimmed copies of EDSs may be based on andinclude different EDSs therein. For example, a trimmed copy may beinitially generated and included/stored in another set of SUs.Subsequently, such trimmed copy can be fully built out to include all ofthe EDSs of a set of EDSs in a set of SUs in which a trimmed copy ofEDSs is initially stored. In some examples, such completion of a trimmedset of EDSs to generate a full copy set of EDSs may be made later whenDSN conditions may be more amendable to do so (e.g., less traffic,period of lower activity, freed up processing resources, etc.). Inaddition, note that as certain versions of EDSs get updated (e.g., whenthe information dispersal algorithm (IDA), or original version of EDSs,or baseline set of EDSs, etc. gets updated), then other versions (e.g.,copies of those EDSs, trimmed copies of those EDSs, etc.) can be updatedappropriately in accordance with the various operations and conditionsas described herein. This disclosure presents a novel means by whichvarious sets of EDSs including copies and/or trimmed copies of EDSs of abaseline set of EDSs can be synchronized in terms of version level amongother characteristics. When one or more SUs store EDSs that are not of acurrent version, then that SU can be directed to perform by another SUand/or computing device or can perform independently a rebuild of thoseEDSs at the proper revision level and/or request such proper revisionlevel EDSs from another one or more SUs that store the proper revisionlevel of EDSs.

In some examples, when the data access request slice name comparesunfavorably with the plurality of slice names, the computing device 12or 16 generates the empty data access response that includes no EDSwithout accessing the HDD. In some examples, note that the computingdevice is located at a first premises that is remotely located from atleast one storage unit (SU) of a plurality of storage units (SUs) withinthe DSN that distributedly store a set of EDSs that includes the EDSassociated with the data object. Note that the computing device 12 or 16may be any type of devices including a storage unit (SU) within the DSN,a wireless smart phone, a laptop, a tablet, a personal computers (PC), awork station, and/or a video game device. Note also that the DSN may beimplemented to include or be based on any of a number of different typesof communication systems including a wireless communication system, awire lined communication systems, a non-public intranet system, a publicinternet system, a local area network (LAN), and/or a wide area network(WAN).

FIG. 12 is a diagram illustrating an embodiment of a method 1200 forexecution by one or more computing devices in accordance with thepresent invention.

The method 1200 begins in step 1210 by receiving (e.g., via an interfaceconfigured to interface and communicate with a dispersed storage network(DSN)) from another computing device a data access request for anencoded data slice (EDS) associated with a data object. Note that thedata access request includes a data access request slice name for theEDS associated with the data object.

The method 1200 continues in step 1220 by comparing the data accessrequest slice name with a plurality of slice names stored within randomaccess memory (RAM) of the computing device. Note that the plurality ofslice names are respectively associated with a plurality of encoded dataslices (EDSs) stored within the HDD.

The method 1200 then operates in step 1230 by determining whether thedata access request slice name compares favorably or unfavorably withthe plurality of slice names.

When the data access request slice name compares unfavorably with theplurality of slice names, the method 1200 then continues in step 1240 bytransmitting via the interface an empty data access response thatincludes no EDS to the other computing device. Alternatively, when thedata access request slice name compares favorably with at least one ofthe plurality of slice names, the method 1200 then continues in step1250 by retrieving, from an hard disk drive (HDD) of the computingdevice, an EDS of the plurality of EDSs having a corresponding slicename that compares favorably with the data access request slice name.Then, the method 1200 then continues in step 1260 by transmitting viathe interface a data access response that includes the EDS of theplurality of EDSs having the corresponding slice name to the othercomputing device.

When a dispersed storage (DS) unit has fast-access memory devicesavailable, but with insufficient capacity to store all slices, it mayuse those fast-access memory devices to store slice names and revisions.This enables rapid responses to be generated for listing requests, checkrequests, and read requests for slices which do not exist. The DS unit,upon receiving a read request, will first check the fast-access memorydevice to determine the list of revisions which it stores for therequested slice name. If it determines that no such revisions are heldon this DS unit, it can immediately return an empty read responsewithout having to incur any IO to the memory devices for which theinput/output (I/O) operations and processing may be expensive (e.g., interms of speed, latency, etc.). The capability to efficiently handlereads for non-existent slices is important to a number of features,including Trimmed Writes, Target Widths, information dispersal algorithm(IDA)+Copy, and other situations. Fast check responses (e.g., veryquickly provided response(s) from a device based on that device making adetermination of status of EDS(s) stored therein by accessinginformation stored in fast memory indicating whether the requestedEDS(s) and/or appropriate revision level(s) are stored therein) areuseful for guaranteeing consistency and for meeting Read Thresholdcheaply, while fast list request responses aid in rebuild scanning,reallocation, rebalancing, and synching between mirrored vaultoperations.

In general, there can be many operations performed within a DSN withoutneeding to read an actual EDS. As such, the slice name(s) may beimplemented in fast access memory (e.g., solid state, RAM, etc. memoryvs. hard disk drive (HDD) memory). As such, the computing device canrespond much more quickly by using slice names and appropriate revisionlevel before accessing the actual storage medium (e.g., HDD) and gettingthe actual data (e.g., EDS(s)).

For example, each computing device and/or SU can be implemented to havea substantial amount of fast memory (e.g., RAM, solid state memory,etc.). There is a dividing line between RAM and HDDs within thecomputing device and/or SU. For example, the computing device and/or SUincludes RAM that is used for processing, but then the computing deviceand/or SU also uses solid state for storage of slice names as well. Thecomputing device and/or SU includes a mapping of where, for each of theslices, are physically stored the slice names and where the actualslices are stored in the device (e.g., in the HDD). As such, thecomputing device and/or SU includes 2 types of memory within the device(e.g., fast memory such as RAM, solid state memory, etc. and memory suchas HDD). The computing device and/or SU puts the slice names (andrevision numbers) in the fast memory and the actual data in the HDD. Thecomputing device and/or SU can respond immediately to any data accessrequests if does not have the data without having to check or access theHDD by checking the slice names in the fast memory such as RAM, solidstate memory, etc. In addition, note that the computing device and/or SUmay also bifurcate the processing such that the computing device and/orSU could have implemented dedicated processing for messaging requests,etc. and then additional processing (and hardware) to access the actualdata (input/output requests).

FIG. 13 is a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes the network 24 of FIG. 1,a set of storage units 1-8 such as based on SUs 36 such as with respectto FIG. 3 or FIG. 7, and the distributed storage and task (DST)processing unit 16 that may be implemented utilizing the computingdevice 12, 14, 16, the managing unit 18, and/or the integrity processingunit 20 such as with respect to FIG. 1, a SU 36 such as with respect toFIG. 3 or FIG. 7, and/or any other device implemented within a DSN toperform operations associated with a DST processing unit. The DSTprocessing unit 16 includes the DST client module 34 and a memory. Thememory may be implemented utilizing the memory 88 of FIG. 3. Eachstorage unit may be implemented utilizing the DST execution unit thatmay be implemented utilizing the computing device 12, 14, 16, themanaging unit 18, and/or the integrity processing unit 20 such as withrespect to FIG. 1, a SU 36 such as with respect to FIG. 3 or FIG. 7,and/or any other device implemented within a DSN to perform operationsassociated with a DST execution unit. A first portion of the set ofstorage units are implemented along with the DST processing unit 16 at afirst site and remaining storage units of the set of storage units areimplemented at a second site, where the first portion of storage unitsare operably coupled to the DST processing unit 16 by a local areanetwork (LAN). The network 24 may include the LAN.

The first portion of the set of storage units includes less than adecode threshold number of storage units, where data A is dispersedstorage error encoded to produce at least one set of an IDA width numberof encoded data slices 1-8, where a decode threshold number of encodeddata slices of each of the at least one set of encoded data slices arerequired to reproduce the data, and where the at least one set ofencoded data slices is stored in the set of storage units such that lessthan the decode threshold number of encoded data slices are storedwithin the first portion of storage units of the first site. The DSNfunctions to enhance data retrieval performance.

In an example of operation of the enhanced data retrieval, where one ormore encoded data slices of each of the one or more sets of encoded dataslices are cached in the memory as cached encoded data slices, where oneor more encoded data slices of the set of encoded data slices are storedin one or more local storage units (e.g., the first portion of storageunits 1-4 at the site 1), and where remaining encoded data slices of theset of encoded data slices are stored in one or more remote storageunits (e.g., storage units 5-8 and the site 2), the DST client module 34retrieves one or more cached encoded data slices of the set of encodeddata slices from the memory. The retrieving includes identifyingavailable Encoded data slices and retrieving the identified availablecash encoded data slices from the memory. For example, the DSTprocessing unit 34 identifies available encoded data slice 5 andretrieves the encoded data slice 5 from the memory.

Having retrieved the one or more encoded data slices, the DST clientmodule 34 initiates retrieval of a sufficient number of encoded dataslices that are stored in the one or more local storage units to producethe decode threshold number of encoded data slices including theretrieve one or more cached encoded data slices. The initiating includesidentifying the number of the sufficient number of encoded data slicesand retrieving, via the LAN, the identified encoded data slices from theone or more local storage units. The identifying of the sufficientnumber includes computing the sufficient number as the decode thresholdnumber might of the number of retrieved cached encoded data slices(e.g., 5−1=4). For example, the DST client module 34 calculates a needfor four more slices, identifies encoded data slices 1-4 as stored inthe storage units 1-4 and retrieves, via the LAN, the encoded dataslices 1-4 from the local storage units 1-4.

When receiving an insufficient number of encoded data slices within arecovery timeframe, the DST client module 34 retrieves at least some ofthe remaining encoded data slices from the one or more rewards storageunits to produce the decode threshold number of encoded data slices. Theretrieving includes determining a number of the remaining encoded dataslices, issuing read slice requests for the number of remaining encodeddata slices, and receiving the number of remaining encoded data slices.

When receiving the decode threshold number of encoded data slices, theDST client module 34 dispersed storage error decodes the received decodethreshold number of encoded data slices to produce recover data A. Whenupdating the stored data, the DST client module 34 facilitates storageof the updated one or more encoded data slices in the one or more localstorage units such that the decode threshold number of encoded dataslices may be recovered from the memory and the one or more localstorage units.

FIG. 14 is a flowchart illustrating an example of enhancing dataretrieval performance. The method 1400 includes a step 1410 where aprocessing module (e.g., of a distributed storage and task (DST) clientmodule), when recovering stored data from a DSN, where the data isstored as a set of encoded data slices retrieves one or more cachedencoded data slices of the set of encoded data slices from a local cachememory. The data is dispersed storage error encoded to produce one ormore sets of encoded data slices, where one or more encoded data slicesof each set of encoded data slices is cached in the local cache memoryas cached encoded data slices, where one or more encoded data slices ofthe set of encoded data slices are stored in one or more local storageunits, where remaining encoded data slices of the set of encoded dataslices are stored in one or more of storage units, and where a decodethreshold number of encoded data slices of the set of encoded dataslices are required to recover the data. The retrieving includesidentifying available cached encoded data slices and retrieving theidentified available cached encoded data slices from the local cachememory.

The method 1400 continues at the step 1420 where the processing moduleinitiates retrieval of a sufficient number of encoded data slices storedin the one or more local storage units to attempt to produce a total ofa decode threshold number of encoded data slices of the set of encodeddata slices. The initiating includes identifying the decode thresholdnumber, determining a number of the sufficient number of encoded dataslices for retrieval, and a determined number of encoded data slicesfrom the one or more local storage units.

When receiving an insufficient number of encoded data slices within aretrieval timeframe, the method 1400 continues at the step 1430 wherethe processing module retrieves remaining encoded data slices of thedecode threshold number of encoded data slices from one or more remotestorage units. The retrieving includes determining a number of remainingencoded data slices, issuing read slice requests for the number ofremaining encoded data slices to the one or more remote storage units,and receiving the number of remaining encoded data slices. Whenreceiving the decode threshold number of encoded data slices, the method1400 continues at step 1040 where the processing module disperse storageerror decodes the received decode threshold number of encoded dataslices to produce recovered data.

FIG. 15 is a schematic block diagram of another embodiment 1500 of a DSNin accordance with the present invention. A computing device 12 or 16includes at least one memory (e.g., memory 1512 and/or memory 1522). Thememory 1512 may be implemented to store encoded data slices (EDSs)and/or operational instructions for use by a processing module of thecomputing device 12 or 16. In some examples, the memory 1512 stores theEDSs, and another memory 1522 stores the operational instructions foruse by a processing module of the computing device 12 or 16. Thecomputing device 12 or 16 is in communication with different respectiveSUs (e.g., first SU(s) 1510 that includes one or more SUs 36, secondSU(s) 1520 that includes one or more SUs 36, third SU(s) 1510 thatincludes one or more SUs 36, etc.). Note that different respective EDSs(e.g., SN and EDS of various numbers) may be stored in differentrespective SUs throughout the DSN. The computing device 12 or 16 is incommunication with the first SU(s) 1510 via a local network 1524 and isin communication with the second SU(s) 1520 and the third SU(s) 1530 viaa local network 1526. Note that each SU(s) 1510, 1520, and 1530 maystore different respective EDSs (e.g., SN and EDS of various numbers. Inone example, that SU(s) 1510 store SN 1_1, EDS 1_1 through SN 1_Y, EDS1_Y, and SU(s) 1120 store SN 2_1, EDS 2_1 through SN 2_Y, EDS 2_Y, andSU(s) 1120 store SN 4_1, EDS 4_1 through SN 4_Y, EDS 4_Y.

In another example, that SU(s) 1510 store SN 1_1, EDS 1_1 through SN1_Y, EDS 1_Y and SN 2_1, EDS 2_1 through SN 2_Y, EDS 2_Y, and SU(s) 1120store SN 2_1, EDS 2_1 through SN 2_Y, EDS 2_Y and SN 3_1, EDS 3_1through SN 3_Y, EDS 3_Y, and SU(s) 1120 store SN 4_1, EDS 4_1 through SN4_Y, EDS 4_Y through SN 5_1, EDS 5_1 through SN 5_Y, EDS 5_Y. In someexamples, approximately 1/n (where n is a positive integer such asgreater than or equal to 2) of the EDSs of a set of EDSs are stored ineach of the SU(s) 1510, 1520, and so on.

In an example of operation and implementation, a computing deviceincludes an interface configured to interface and communicate with adispersed storage network (DSN), a memory that stores operationalinstructions, and a processing module operably coupled to the interfaceand memory such that the processing module, when operable within thecomputing device based on the operational instructions, is configured toperform various operations.

In an example, the computing device 12 of 16 receives a data accessrequest involving a set of EDSs associated with a data object that aredistributedly stored among a plurality of storage units (SUs) thatincludes a first at least one SU that is coupled to the computing devicevia a local network of the DSN and a second at least one SU that isremotely located to the computing device and is coupled to the computingdevice via an external network of the DSN.

Note that the data object is segmented into a plurality of datasegments, and a data segment of the plurality of data segments isdispersed error encoded in accordance with dispersed error encodingparameters to produce the set of EDSs. A decode threshold number of EDSsare needed to recover the data segment, a read threshold number of EDSsprovides for reconstruction of the data segment, and a write thresholdnumber of EDSs provides for a successful transfer of the set of EDSsfrom a first at least one location in the DSN to a second at least onelocation in the DSN.

The computing device 12 of 16 then caches within the at least one memory(e.g., memory 1512) a subset of EDSs stored within the second at leastone SU that is remotely located to the computing device and is coupledto the computing device via the external network 1526 (e.g., SU(s)1520). The computing device 12 of 16 then processes the data accessrequest involving the set of EDSs associated with the data object basedon a first at least one EDS of the set of EDSs stored within the firstat least one SU via the local network (e.g., SU(s) 1520) and based on asecond at least one EDS of the set of EDSs stored within the at leastone memory of the computing device (e.g., memory 1512) and/or a third atleast one EDS of the set of EDSs stored within the second at least oneSU via the external network (e.g., SU(s) 1530).

In some examples, the computing device 12 of 16 retrieves firstly thesecond at least one EDS of the set of EDSs stored within the at leastone memory of the computing device, then retrieves secondly the first atleast one EDS of the set of EDSs stored within the first at least one SUvia the local network, and retrieves thirdly the third at least one EDSof the set of EDSs stored within the second at least one SU via theexternal network.

Also, in other examples, the computing device 12 or 16 is configured toprocess the data access request involving the set of EDSs associatedwith the data object including to retrieve the decode threshold numberof EDSs, the read threshold number of EDSs, and/or the write thresholdnumber of EDSs from the first at least one EDS of the set of EDSs storedwithin the first at least one SU via the local network and the second atleast one EDS of the set of EDSs stored within the at least one memoryof the computing device.

Also, in even other examples, the computing device 12 or 16 operates todetermine a first revision level of a first EDS having a slice name ofthe set of EDSs stored within the first at least one SU with a secondrevision level of a second EDS having the slice name of the set of EDSsstored within the at least one memory of the computing device. Then,when the first revision level compares unfavorably to the secondrevision level, the computing device 12 or 16 operates to request fromthe first at least one SU the first EDS having the slice name of the setof EDSs stored within the first at least one SU to replace the secondEDS having the slice name of the set of EDSs stored within the at leastone memory of the computing device.

In some examples, the computing device 12 or 16 operates to process thedata access request involving the set of EDSs associated with the dataobject such that the set of EDSs associated with the data aredistributedly stored among the plurality of SUs that includes n SUs,wherein n is a positive integer greater than or equal to 2, such that afirst approximately 1/n EDSs are stored within the first at least one SUand a second approximately 1/n EDSs are stored within the second atleast one SU. Then, the computing device 12 or 16 operates to cachewithin the at least one memory a sufficient number of EDSs stored withinthe second at least one SU that is remotely located to the computingdevice and is coupled to the computing device via the external networkso that at least one of the decode threshold number of EDSs, the readthreshold number of EDSs, or the write threshold number of EDSs may beretrieved from the at least one memory and the first at least one SU.

Note that the computing device may be located at a first premises thatis remotely located from at least one SU of the primary SUs or pluralityof secondary SUs the within the DSN. Also, note that the computingdevice may be of any of a variety of types of devices as describedherein and/or their equivalents including a SU of any group and/or setof SUs within the DSN, a wireless smart phone, a laptop, a tablet, apersonal computers (PC), a work station, and/or a video game device.Note also that the DSN may be implemented to include or be based on anyof a number of different types of communication systems including awireless communication system, a wire lined communication systems, anon-public intranet system, a public internet system, a local areanetwork (LAN), and/or a wide area network (WAN).

FIG. 16A is a diagram illustrating an embodiment of a method 1601 forexecution by one or more computing devices in accordance with thepresent invention.

The method 1601 begins in step 1610 by receiving, via an interfaceconfigured to interface and communicate with a dispersed storage network(DSN), a data access request involving a set of encoded data slices(EDSs) associated with a data object. In some examples, the EDS aredistributedly stored among a plurality of storage units (SUs) thatincludes a first at least one SU that is coupled to the computing devicevia a local network of the DSN as shown in step 1612 and a second atleast one SU that is remotely located to the computing device and iscoupled to the computing device via an external network of the DSN asshown in step 1614.

The method 1601 continues in step 1620 by caching within at least onememory of the computing device a subset of EDSs stored within the secondat least one SU that is remotely located to the computing device and iscoupled to the computing device via the external network.

The method 1601 then operates in step 1630 by processing the data accessrequest involving the set of EDSs associated with the data object basedon a first at least one EDS of the set of EDSs stored within the firstat least one SU via the local network and based on at least one of asecond at least one EDS of the set of EDSs stored within the at leastone memory of the computing device or a third at least one EDS of theset of EDSs stored within the second at least one SU via the externalnetwork.

FIG. 16B is a diagram illustrating an embodiment of another method 1602for execution by one or more computing devices in accordance with thepresent invention. Such operations of the method 1602 may involveprocessing the data access request involving the set of EDSs associatedwith the data object. The method 1602 begins in step 1611 by retrievingfirstly the second at least one EDS of the set of EDSs stored within theat least one memory of the computing device. The method 1602 continuesin step 1621 by retrieving secondly the first at least one EDS of theset of EDSs stored within the first at least one SU via the localnetwork. The method 1602 then operates in step 1631 by retrievingthirdly the third at least one EDS of the set of EDSs stored within thesecond at least one SU via the external network.

FIG. 16C is a diagram illustrating an embodiment of another method 1603for execution by one or more computing devices in accordance with thepresent invention.

The method 1603 begins in step 1612 by determining a first revisionlevel of a first EDS having a slice name of the set of EDSs storedwithin the first at least one SU with a second revision level of asecond EDS having the slice name of the set of EDSs stored within the atleast one memory of the computing device. The method 1603 continues instep 1624 by determining whether the first revision level comparesunfavorably to the second revision level. When the first revision levelcompares unfavorably to the second revision level, the method 1603 thenoperates in step 1626 by requesting from the first at least one SU thefirst EDS having the slice name of the set of EDSs stored within thefirst at least one SU to replace the second EDS having the slice name ofthe set of EDSs stored within the at least one memory of the computingdevice.

A DS processing unit might cache entire segments or objects restored viathe information dispersal algorithm (IDA) to enable efficient reads ofthose segments or objects. However, depending on the location of the DSprocessing unit, this may be a non-optimal use of the DS processingunits memory. A DS unit deployed at one of the sites of a three-site DSNmemory has access to ⅓rd of the DS units with site-local networklatencies and speeds. An optimized DS processing unit might thereforecache only ⅔rds of an IDA threshold number of slices, with those slicescorresponding to slices held by DS units at remote sites. Therefore ituses only ⅔rds the memory necessary to cache that full segment, set ofEDSs, and/or object (thereby enabling it to cache 50% moresegments/objects) than it otherwise would have been capable of cachingfor the same amount of memory. Upon a request for any object for whichit contains slices in cache, the DS processing unit will issue localreads to ⅓rd IDA Threshold number of the DS processing at the same siteas the DS processing unit. In general, such an implementation may bebased on n-site (where n is a positive integer, such as greater than orequal to 2) DSN memory has access to 1/n of the DS units with site-localnetwork latencies and speeds. An optimized DS processing unit mighttherefore cache only 2/n or (3/n, 4/n, or so on) of an IDA thresholdnumber of slices, with those slices corresponding to slices held by DSunits at remote sites. Therefore it uses only 2/n (or 3/m, 4/n, or soon) the memory necessary to cache that full segment or object (therebyenabling it to cache 50% more segments/objects) than it otherwise wouldhave been capable of caching for the same amount of memory. Upon arequest for any object for which it contains slices in cache, the DSprocessing unit will issue local reads to 1/n IDA Threshold number ofthe DS processing at the same site as the DS processing unit

These reads will return very quickly since they go out over the localnetwork of the site. Once the DS processing unit has these additionalslices, it can reassemble the full source from the slices it already hasin cache, and satisfy the request. If, on the other hand, the DSprocessing unit gets slices with revisions different from those in itscache, it will have to issue additional reads to other DS units. It canachieve a threshold of a higher revision slice, then it will invalidatethe slices of the old revision in its cache, and replace them withrevisions of the new slices from the remote DS units it retrieved and/orre-generated, rebuilt, etc. To make this novel strategy even moreresilient with only a slight increase in memory, the DS processing unitmay cache a few additional slices corresponding to DS units remote fromits site (e.g., EDSs from one or more SUs that are remotely locatedthere from such as via an external network). Therefore if some local DSunits fail, it will remain capable of satisfying requests using the fewextra remote slices in its cache.

In a specific example, consider a DSN that stores 500 clients that areall requesting the same data over and over again. The DSN is implementedsuch that at least one device can locally store some information (e.g.,EDSs). Also, instead of storing all information (e.g., EDSs), the DSNmay be implemented to keep some information (e.g., EDSs) stored locallyand keep it decoded in the local station for security. This way, even ifa bad agent were to hack into the system, that bad agent could notretrieve the data because it is encoded format.

A computing device can be implemented in the same local network as atleast one other SU (e.g., have a local network connection to that atleast one SU), and the computing device can have that other SU storesome if its information. Also, the computing device can use this aschecks and balances (e.g., checking the revision higher from an SU onthe local network, and then know that is locally stored copy isoutdated).

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A storage unit comprising: an interfaceconfigured to interface and communicate with a storage network; memorythat stores operational instructions; and a processing module operablycoupled to the interface and to the memory, wherein the processingmodule, when operable within the storage unit based on the operationalinstructions, is configured to: receive, via the storage network, a dataaccess request for an encoded data slice associated with a data object;determine whether the encoded data slice is stored in a first memory;and in response to a determination that the encoded data slice is notstored in the first memory: issue another data access request for theencoded data slice to a second memory, wherein the first memory includesaccess characteristics that are faster than the second memory; receive adata access response from the second memory, wherein the data accessresponse includes the encoded data slice; and transmit a response, viathe storage network, wherein the response includes the encoded dataslice.
 2. The storage unit of claim 1, wherein the processing module isfurther configured to: in response to a determination that the encodeddata slice is stored in the first memory: retrieve the encoded dataslice from the first memory; and transmit a response, via the storagenetwork, wherein the response includes the encoded data slice.
 3. Thestorage unit of claim 1, wherein the processing module is furtherconfigured to: store the encoded data slice in the first memory.
 4. Thestorage unit of claim 1, wherein the data access request includes anencoded data slice identifier for the encoded data slice.
 5. The storageunit of claim 4, wherein the determination whether the encoded dataslice is stored in the second memory is based on the encoded data sliceidentifier.
 6. The storage unit of claim 4, wherein the processingmodule is further configured to: compare the encoded data sliceidentifier with a plurality of encoded data slice identifiers storedwithin the second memory, wherein the plurality of encoded data sliceidentifiers are associated with a corresponding plurality of encodeddata slices stored within the first memory.
 7. The storage unit of claim6, wherein the plurality of encoded data slice identifiers stored withinthe second memory are associated with a corresponding plurality ofencoded data slices stored within the first memory of the storage unit.8. The storage unit of claim 7, wherein each encoded data sliceidentifier of the plurality of corresponding encoded data sliceidentifiers stored in the first memory includes information sufficientto identify a revision for a plurality of encoded data slices stored inthe second memory.
 9. The storage unit of claim 6, wherein the transmita response is dependent on the data access response from the secondmemory being received within a predetermined time window, wherein theresponse is not transmitted if the data access response from the secondmemory is received outside the predetermined time window.
 10. A methodfor execution by a computing device, the method comprising: receiving,via an interface of the computing device configured to interface andcommunicate with a storage network, a data access request for an encodeddata slice associated with a data object; determining whether theencoded data slice is stored in a first memory; and in response to adetermination that the encoded data slice is not stored in the firstmemory: issuing another data access request for the encoded data sliceto a second memory, wherein the first memory includes accesscharacteristics that are faster than the second memory; receiving a dataaccess response from the second memory, wherein the data access responseincludes the encoded data slice; and transmitting a response, via thestorage network, wherein the response includes the encoded data slice.11. The method of claim 10, further comprising: in response to adetermination that the encoded data slice is stored in the first memory:retrieving the encoded data slice from the first memory; andtransmitting a response, via the storage network, wherein the responseincludes the encoded data slice.
 12. The method of claim 10, furthercomprising: storing the encoded data slice in the first memory.
 13. Themethod of claim 10, wherein the data access request includes an encodeddata slice identifier for the encoded data slice.
 14. The method ofclaim 13, wherein the determination whether the encoded data slice isstored in the second memory is based on the encoded data sliceidentifier.
 15. The method of claim 14, further comprising: comparingthe encoded data slice identifier with a plurality of encoded data sliceidentifiers stored within the second memory, wherein the plurality ofencoded data slice identifiers are associated with a correspondingplurality of encoded data slices stored within the first memory.
 16. Themethod of claim 15, wherein the plurality of encoded data sliceidentifiers stored within the second memory are associated with acorresponding plurality of encoded data slices stored within the firstmemory of the storage unit.
 17. The method of claim 16, wherein eachencoded data slice identifier of the plurality of corresponding encodeddata slice identifiers stored in the first memory includes informationsufficient to identify a revision for a plurality of encoded data slicesstored in the second memory.
 18. The method of claim 15, wherein thetransmitting a response is dependent on the data access response fromthe second memory being received within a predetermined time window,wherein the response is not transmitted if the data access response fromthe second memory is received outside the predetermined time window. 19.The method of claim 10, wherein the computing device is located at afirst premises that is remotely located from at least one storage unitof a plurality of storage units that includes the storage unit withinthe storage network; wherein the storage distributedly stores a set ofencoded data slices that includes the encoded data slice.
 20. Anon-transient computer readable medium containing program instructionsfor causing a computer to perform the method of: receiving, via aninterface of the computing device configured to interface andcommunicate with a storage network, a data access request for an encodeddata slice associated with a data object; determining whether theencoded data slice is stored in the first memory; and in response to adetermination that the encoded data slice is not stored in the firstmemory: issuing another data access request for the encoded data sliceto a second memory, wherein the first memory includes accesscharacteristics that are faster than the second memory; receiving a dataaccess response from the second memory, wherein the data access responseincludes the encoded data slice; and transmitting a response, via thestorage network, wherein the response includes the encoded data slice.